采用夜光遥感数据提取城市建成区的邻域极值法  

Neighborhood Extremum Method of Extracting Urban Built-Up Area Using Nighttime Lighting Data

作　　者：孙立双 韩耀辉 谢志伟 李如仁 SUN Lishuang;HAN Yaohui;XIE Zhiwei;LI Ruren(School of Transportation Engineering,Shenyang Jianzhu University,Shenyang 110168,China)

机构地区：[1]沈阳建筑大学交通工程学院,辽宁沈阳110168

出　　处：《武汉大学学报（信息科学版）》2020年第10期1619-1625,共7页Geomatics and Information Science of Wuhan University

基　　金：辽宁省教育厅科学研究项目(lnqn201917)。

摘　　要：针对灯光溢出特性导致的采用夜光数据提取城市建成区精度低的问题,提出了采用邻域极值法的建成区提取方法。首先,应用一元二次回归模型对夜光数据进行相对辐射校正处理;然后,通过邻域极值滤波得到描述影像灰度值空间变化特征的极值影像;最后,采用极值搜索算法获取建成区边界影像,并利用二值分割法提取城市建成区。实验结果表明,所提方法的平均Kappa系数和阈值选取时间分别为0.85、37 s,较突变检测法和统计分析法分别提高了0.03、1 503 s和0.01、443 s。提取结果的空间形态更接近于参考数据,具有更好的提取效果和稳定性。To address the problem of low accuracy in the urban built-up area extraction method using nighttime light data due to light spillover characteristics, the build-up area extraction method based on neighborhood extremum is proposed. Firstly, the one-dimensional quadratic regression is used to perform relative radiation correction for nighttime light data. Then, the extremum images describing the spatial variation characteristics of gray values are obtained by extremum neighborhood filtering. Finally, the extremum search algorithm was used to obtain the boundary images of built-up areas, and the binary segmentation method is used to extract urban built-up areas. The experimental results show that the means of Kappa coefficients and threshold selection times of our proposed method are 0.85 and 37 s, which are 0.03, 1 503 s and 0.01, 443 s higher than that of the mutation detection method and the statistical analysis method. The spatial morphology of the built-up area extraction results is closer to the reference data, which has better extraction effect and stability.

关 键 词：灯光溢出特性 夜光数据 邻域极值滤波 极值搜索算法 城市建成区 

分 类 号：P237[天文地球—摄影测量与遥感]